Systems and methods for block noise detection and filtering are disclosed. One embodiment includes, computing difference magnitudes in pixel values for adjacent pixels in the image. The difference magnitudes can include horizontal difference magnitudes for horizontally adjacent pixels and vertical difference magnitudes for vertically adjacent pixels. One embodiment further includes using normalized sums of the difference magnitudes to determine a set of noise characteristics of the block noise and a set of image characteristics of the image and configuring inputs to the block noise filter using the set of noise and image characteristics.
Legal claims defining the scope of protection, as filed with the USPTO.
1. A method for configuring a block noise filter for filtering block noise in an image, the method, comprising: computing difference magnitudes in pixel values for adjacent pixels in the image, wherein the difference magnitudes comprise horizontal difference magnitudes for horizontally adjacent pixels and vertical difference magnitudes for vertically adjacent pixels; using normalized sums of the difference magnitudes to determine a set of noise characteristics of the block noise; using difference magnitude data to determine a set of image characteristics of the image; and configuring inputs to the block noise filter using the set of noise and image characteristics.
2. The method of claim 1 , wherein the inputs to the block noise filter comprise a gain value having a vertical filter gain and a horizontal filter gain, wherein the set of noise characteristics include, strength of block noise and block size, wherein the set of image characteristics include, amount of detail in the image, and wherein the gain value includes a horizontal filter gain and a vertical filter gain.
3. The method of claim 2 , further comprising: increasing the gain value of the block noise filter with increasing strength of block noise; increasing the gain value of the block noise filter with a low amount of detail in the image; and increasing the gain value of the block noise filter with larger block size.
4. The method of claim 1 , wherein the inputs to the block noise filter further comprise an edge gradient multiplier having a horizontal edge multiplier and a vertical edge multiplier.
5. The method of claim 4 , further comprising: decreasing the edge gradient multiplier with increasing strength of block noise; and increasing the edge gradient multiplier with a high amount of detail in the image.
6. The method of claim 1 , further comprising: generating a block boundary map of block noise boundary locations in the image, wherein the block boundary map includes horizontal and vertical boundaries; configuring the block noise filter with the block boundary map, the gain value, and the edge gradient multiplier; applying the block noise filter to the image to generate a filtered image; performing edge-blending on the filtered image; and performing edge-smoothing on the filtered image.
7. An apparatus comprising: an optical disk reader, wherein, when in operation, reads an optical disk; a memory coupled to the optical reader, the memory having stored thereon instructions; and a processing device coupled to the memory, wherein the processing device to execute the instructions which apply a block noise filter to an image by performing one or more operations comprising: computing difference magnitudes in pixel values for adjacent pixels in the image, wherein the difference magnitudes comprise horizontal difference magnitudes for horizontally adjacent pixels and vertical difference magnitudes for vertically adjacent pixels; using normalized sums of the difference magnitudes to determine a set of noise characteristics of the block noise; using difference magnitude data to determine a set of image characteristics of the image; and configuring inputs to the block noise filter using the set of noise and image characteristics.
8. The apparatus of claim 7 , wherein the inputs to the block noise filter comprise a gain value having a vertical filter gain and a horizontal filter gain, wherein the set of noise characteristics include, strength of block noise and block size, wherein the set of image characteristics include, amount of detail in the image, and wherein the gain value includes a horizontal filter gain and a vertical filter gain.
9. The apparatus of claim 8 , wherein the one or more operations comprise: increasing the gain value of the block noise filter with increasing strength of block noise; increasing the gain value of the block noise filter with a low amount of detail in the image; and increasing the gain value of the block noise filter with larger block size.
10. The apparatus of claim 8 , wherein the inputs to the block noise filter further comprise an edge gradient multiplier having a horizontal edge multiplier and a vertical edge multiplier.
11. The apparatus of claim 10 , wherein the one or more operations comprise: decreasing the edge gradient multiplier with increasing strength of block noise; and increasing the edge gradient multiplier with a high amount of detail in the image.
12. The apparatus of claim 7 , wherein the one or more operations comprise: generating a block boundary map of block noise boundary locations in the image, wherein the block boundary map includes horizontal and vertical boundaries; configuring the block noise filter with the block boundary map, the gain value, and the edge gradient multiplier; applying the block noise filter to the image to generate a filtered image; performing edge-blending on the filtered image; and performing edge-smoothing on the filtered image.
13. The apparatus of claim 7 , wherein the optical disk reader comprises one or more of a Blu-ray disk reader, a digital versatile disk (DVD) reader, and a high definition-DVD (HD-DVD) reader, wherein the processing device comprises a graphics processor.
14. A non-transitory machine readable medium having stored thereon instructions which, when executed by a machine, cause the machine to perform one or more operations comprising: computing difference magnitudes in pixel values for adjacent pixels in the image, wherein the difference magnitudes comprise horizontal difference magnitudes for horizontally adjacent pixels and vertical difference magnitudes for vertically adjacent pixels; using normalized sums of the difference magnitudes to determine a set of noise characteristics of the block noise; using difference magnitude data to determine a set of image characteristics of the image; and configuring inputs to the block noise filter using the set of noise and image characteristics.
15. The machine readable medium of claim 14 , wherein the inputs to the block noise filter comprise a gain value of the block noise filter having a vertical filter gain and a horizontal filter gain, wherein the set of noise characteristics include, strength of block noise and block size, wherein the set of image characteristics include, amount of detail in the image, and wherein the gain value includes a horizontal filter gain and a vertical filter gain.
16. The machine readable medium of claim 15 , wherein the one or more operations comprise: increasing the gain value of the block noise filter with increasing strength of block noise; increasing the gain value of the block noise filter with a low amount of detail in the image; and increasing the gain value of the block noise filter with larger block size.
17. The machine readable medium of claim 16 , wherein the inputs to the block noise filter further comprise an edge gradient multiplier having a horizontal edge multiplier and a vertical edge multiplier.
18. The machine readable medium of claim 17 , wherein the one or more operations comprise: decreasing the edge gradient multiplier with increasing strength of block noise; and increasing the edge gradient multiplier with a high amount of detail in the image.
19. The machine readable medium of claim 14 , wherein the one or more operations comprise: generating a block boundary map of block noise boundary locations in the image, wherein the block boundary map includes horizontal and vertical boundaries; configuring the block noise filter with the block boundary map, the gain value, and the edge gradient multiplier; applying the block noise filter to the image to generate a filtered image; performing edge-blending on the filtered image; and performing edge-smoothing on the filtered image.
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May 21, 2013
November 18, 2014
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